COVID-19, Renin-Angiotensin System and Endothelial Dysfunction
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(CD147) Is Induced by C/Ebpβ and Is Differentially Expressed in ALK+
Laboratory Investigation (2017) 97, 1095–1102 © 2017 USCAP, Inc All rights reserved 0023-6837/17 EMMPRIN (CD147) is induced by C/EBPβ and is differentially expressed in ALK+ and ALK − anaplastic large-cell lymphoma Janine Schmidt1, Irina Bonzheim1, Julia Steinhilber1, Ivonne A Montes-Mojarro1, Carlos Ortiz-Hidalgo2, Wolfram Klapper3, Falko Fend1 and Leticia Quintanilla-Martínez1 Anaplastic lymphoma kinase-positive (ALK+) anaplastic large-cell lymphoma (ALCL) is characterized by expression of oncogenic ALK fusion proteins due to the translocation t(2;5)(p23;q35) or variants. Although genotypically a T-cell lymphoma, ALK+ ALCL cells frequently show loss of T-cell-specific surface antigens and expression of monocytic markers. C/EBPβ, a transcription factor constitutively overexpressed in ALK+ ALCL cells, has been shown to play an important role in the activation and differentiation of macrophages and is furthermore capable of transdifferentiating B-cell and T-cell progenitors to macrophages in vitro. To analyze the role of C/EBPβ for the unusual phenotype of ALK+ ALCL cells, C/EBPβ was knocked down by RNA interference in two ALK+ ALCL cell lines, and surface antigen expression profiles of these cell lines were generated using a Human Cell Surface Marker Screening Panel (BD Biosciences). Interesting candidate antigens were further analyzed by immunohistochemistry in primary ALCL ALK+ and ALK − cases. Antigen expression profiling revealed marked changes in the expression of the activation markers CD25, CD30, CD98, CD147, and CD227 after C/EBPβ knockdown. Immunohistochemical analysis confirmed a strong, membranous CD147 (EMMPRIN) expression in ALK+ ALCL cases. In contrast, ALK − ALCL cases showed a weaker CD147 expression. -
Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo -
Single-Cell RNA Sequencing Demonstrates the Molecular and Cellular Reprogramming of Metastatic Lung Adenocarcinoma
ARTICLE https://doi.org/10.1038/s41467-020-16164-1 OPEN Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma Nayoung Kim 1,2,3,13, Hong Kwan Kim4,13, Kyungjong Lee 5,13, Yourae Hong 1,6, Jong Ho Cho4, Jung Won Choi7, Jung-Il Lee7, Yeon-Lim Suh8,BoMiKu9, Hye Hyeon Eum 1,2,3, Soyean Choi 1, Yoon-La Choi6,10,11, Je-Gun Joung1, Woong-Yang Park 1,2,6, Hyun Ae Jung12, Jong-Mu Sun12, Se-Hoon Lee12, ✉ ✉ Jin Seok Ahn12, Keunchil Park12, Myung-Ju Ahn 12 & Hae-Ock Lee 1,2,3,6 1234567890():,; Advanced metastatic cancer poses utmost clinical challenges and may present molecular and cellular features distinct from an early-stage cancer. Herein, we present single-cell tran- scriptome profiling of metastatic lung adenocarcinoma, the most prevalent histological lung cancer type diagnosed at stage IV in over 40% of all cases. From 208,506 cells populating the normal tissues or early to metastatic stage cancer in 44 patients, we identify a cancer cell subtype deviating from the normal differentiation trajectory and dominating the metastatic stage. In all stages, the stromal and immune cell dynamics reveal ontological and functional changes that create a pro-tumoral and immunosuppressive microenvironment. Normal resident myeloid cell populations are gradually replaced with monocyte-derived macrophages and dendritic cells, along with T-cell exhaustion. This extensive single-cell analysis enhances our understanding of molecular and cellular dynamics in metastatic lung cancer and reveals potential diagnostic and therapeutic targets in cancer-microenvironment interactions. 1 Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Flow Reagents Single Color Antibodies CD Chart
CD CHART CD N° Alternative Name CD N° Alternative Name CD N° Alternative Name Beckman Coulter Clone Beckman Coulter Clone Beckman Coulter Clone T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells T Cells B Cells Granulocytes NK Cells Macrophages/Monocytes Platelets Erythrocytes Stem Cells Dendritic Cells Endothelial Cells Epithelial Cells CD1a T6, R4, HTA1 Act p n n p n n S l CD99 MIC2 gene product, E2 p p p CD223 LAG-3 (Lymphocyte activation gene 3) Act n Act p n CD1b R1 Act p n n p n n S CD99R restricted CD99 p p CD224 GGT (γ-glutamyl transferase) p p p p p p CD1c R7, M241 Act S n n p n n S l CD100 SEMA4D (semaphorin 4D) p Low p p p n n CD225 Leu13, interferon induced transmembrane protein 1 (IFITM1). p p p p p CD1d R3 Act S n n Low n n S Intest CD101 V7, P126 Act n p n p n n p CD226 DNAM-1, PTA-1 Act n Act Act Act n p n CD1e R2 n n n n S CD102 ICAM-2 (intercellular adhesion molecule-2) p p n p Folli p CD227 MUC1, mucin 1, episialin, PUM, PEM, EMA, DF3, H23 Act p CD2 T11; Tp50; sheep red blood cell (SRBC) receptor; LFA-2 p S n p n n l CD103 HML-1 (human mucosal lymphocytes antigen 1), integrin aE chain S n n n n n n n l CD228 Melanotransferrin (MT), p97 p p CD3 T3, CD3 complex p n n n n n n n n n l CD104 integrin b4 chain; TSP-1180 n n n n n n n p p CD229 Ly9, T-lymphocyte surface antigen p p n p n -
Molecular Characteristics of Circulating Tumor Cells Resemble the Liver Metastasis More Closely Than the Primary Tumor in Metastatic Colorectal Cancer
www.impactjournals.com/oncotarget/ Oncotarget, Vol. 7, No. 37 Research Paper Molecular characteristics of circulating tumor cells resemble the liver metastasis more closely than the primary tumor in metastatic colorectal cancer Wendy Onstenk1, Anieta M. Sieuwerts1, Bianca Mostert1, Zarina Lalmahomed2, Joan B. Bolt-de Vries1, Anne van Galen1, Marcel Smid1, Jaco Kraan1, Mai Van1, Vanja de Weerd1, Raquel Ramírez-Moreno1, Katharina Biermann3, Cornelis Verhoef2, Dirk J. Grünhagen2, Jan N.M. IJzermans2, Jan W. Gratama1, John W.M. Martens1, John A. Foekens1, Stefan Sleijfer1 1Erasmus MC Cancer Institute, Department of Medical Oncology and Cancer Genomics Netherlands, Rotterdam, The Netherlands 2Department of Surgery, Erasmus University Medical Center, Rotterdam, The Netherlands 3Department of Pathology, Erasmus University Medical Center, Rotterdam, The Netherlands Correspondence to: Wendy Onstenk, email: [email protected] Keywords: circulating tumor cells, CTCs, CellSearch, colorectal cancer, gene expression profiling Received: April 06, 2016 Accepted: May 29, 2016 Published: June 20, 2016 ABSTRACT Background: CTCs are a promising alternative for metastatic tissue biopsies for use in precision medicine approaches. We investigated to what extent the molecular characteristics of circulating tumor cells (CTCs) resemble the liver metastasis and/ or the primary tumor from patients with metastatic colorectal cancer (mCRC). Results: The CTC profiles were concordant with the liver metastasis in 17/23 patients (74%) and with the primary tumor in 13 patients (57%). The CTCs better resembled the liver metastasis in 13 patients (57%), and the primary tumor in five patients (22%). The strength of the correlations was not associated with clinical parameters. Nine genes (CDH1, CDH17, CDX1, CEACAM5, FABP1, FCGBP, IGFBP3, IGFBP4, and MAPT) displayed significant differential expressions, all of which were downregulated, in CTCs compared to the tissues in the 23 patients. -
Systemic Surfaceome Profiling Identifies Target Antigens for Immune-Based Therapy in Subtypes of Advanced Prostate Cancer
Systemic surfaceome profiling identifies target antigens for immune-based therapy in subtypes of advanced prostate cancer John K. Leea,b,c, Nathanael J. Bangayand, Timothy Chaie, Bryan A. Smithf, Tiffany E. Parivaf, Sangwon Yung, Ajay Vashishth, Qingfu Zhangi,j, Jung Wook Parkf, Eva Coreyk, Jiaoti Huangi, Thomas G. Graeberc,d,l,m, James Wohlschlegelh, and Owen N. Wittec,d,f,n,o,1 aDivision of Hematology and Oncology, Department of Medicine, University of California, Los Angeles, CA 90095; bInstitute of Urologic Oncology, Department of Urology, University of California, Los Angeles, CA 90095; cJonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095; dDepartment of Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095; eStanford University School of Medicine, Palo Alto, CA 94305; fDepartment of Microbiology, Immunology, and Medical Genetics, University of California, Los Angeles, CA 90095; gYale School of Medicine, New Haven, CT 06510; hDepartment of Biological Chemistry, University of California, Los Angeles, CA 90095; iDepartment of Pathology, Duke University School of Medicine, Durham, NC 27708; jDepartment of Pathology, China Medical University, 110001 Shenyang, People’s Republic of China; kDepartment of Urology, University of Washington School of Medicine, Seattle, WA 98195; lCrump Institute for Molecular Imaging, University of California, Los Angeles, CA 90095; mUCLA Metabolomics Center, University of California, Los Angeles, CA 900095; nParker Institute for Cancer Immunotherapy, -
Downloaded by Academic Researchers from Academia.Nferx.Com and Will Be Made Accessible to Non-Academic Researchers Upon Reasonable Request
G C A T T A C G G C A T genes Article A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets Deeksha Doddahonnaiah 1,†, Patrick J. Lenehan 1,† , Travis K. Hughes 1, David Zemmour 1, Enrique Garcia-Rivera 1 , A. J. Venkatakrishnan 1, Ramakrishna Chilaka 2, Apoorv Khare 2, Akhil Kasaraneni 2, Abhinav Garg 2, Akash Anand 2, Rakesh Barve 2, Viswanathan Thiagarajan 2 and Venky Soundararajan 1,2,* 1 nference, One Main Street, Cambridge, MA 02142, USA; [email protected] (D.D.); [email protected] (P.J.L.); [email protected] (T.K.H.); [email protected] (D.Z.); [email protected] (E.G.-R.); [email protected] (A.J.V.) 2 nference Labs, Bengaluru, Karnataka 560017, India; [email protected] (R.C.); [email protected] (A.K.); [email protected] (A.K.); [email protected] (A.G.); [email protected] (A.A.); [email protected] (R.B.); [email protected] (V.T.) * Correspondence: [email protected] † These authors contributed equally. Abstract: Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been Citation: Doddahonnaiah, D.; adequately explored. Here we deployed an NLP framework to objectively quantify associations Lenehan, P.J.; Hughes, T.K.; between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type Zemmour, D.; Garcia-Rivera, E.; terms across over 26 million biomedical documents. -
No Evidence for Basigin/CD147 As a Direct SARS-Cov-2 Spike
www.nature.com/scientificreports OPEN No evidence for basigin/CD147 as a direct SARS‑CoV‑2 spike binding receptor Jarrod Shilts 1*, Thomas W. M. Crozier 2, Edward J. D. Greenwood2, Paul J. Lehner 2 & Gavin J. Wright 1,3* The spike protein of SARS‑CoV‑2 is known to enable viral invasion into human cells through direct binding to host receptors including ACE2. An alternate entry receptor for the virus was recently proposed to be basigin/CD147. These early studies have already prompted a clinical trial and multiple published hypotheses speculating on the role of this host receptor in viral infection and pathogenesis. Here, we report that we are unable to fnd evidence supporting the role of basigin as a putative spike binding receptor. Recombinant forms of the SARS‑CoV‑2 spike do not interact with basigin expressed on the surface of human cells, and by using specialized assays tailored to detect receptor interactions as weak or weaker than the proposed basigin‑spike binding, we report no evidence for a direct interaction between the viral spike protein to either of the two common isoforms of basigin. Finally, removing basigin from the surface of human lung epithelial cells by CRISPR/Cas9 results in no change in their susceptibility to SARS‑CoV‑2 infection. Given the pressing need for clarity on which viral targets may lead to promising therapeutics, we present these fndings to allow more informed decisions about the translational relevance of this putative mechanism in the race to understand and treat COVID‑19. Te sudden emergence of SARS-CoV-2 in late 2019 has demanded extensive research be directed to resolve the many uncharted aspects of this previously-unknown virus. -
The Immunomodulatory CEA Cell Adhesion Molecule 6 (CEACAM6/Cd66c) Is a Candidate Receptor for the Influenza a Virus
bioRxiv preprint doi: https://doi.org/10.1101/104026; this version posted January 30, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 The immunomodulatory CEA cell adhesion molecule 6 (CEACAM6/CD66c) is a 2 candidate receptor for the influenza A virus 3 Shah Kamranur Rahmana *, Mairaj Ahmed Ansarib, Pratibha Gaurc, Imtiyaz Ahmada, 4 Chandrani Chakravartya,d, Dileep Kumar Vermaa, Sanjay Chhibbere, Naila Nehalf, 5 Shanmugaapriya Sellathanbyd, Dagmar Wirthc, Gulam Warisb and Sunil K. Lala,g # 6 7 Virology Group, International Centre for Genetic Engineering & Biotechnology, New Delhi, 8 Indiaa. 9 Department of Microbiology and Immunology, H. M. Bligh Cancer Research Laboratories, 10 Rosalind Franklin University of Medicine and Science, Chicago Medical School, North 11 Chicago, Illinois, USAb. 12 Helmholtz Centre for Infection Research, Braunschweig, Germanyc. 13 Department of Biomedical Science, Bharathidasan University, Trichy, Indiad. 14 Microbiology Department, Panjab University, Chandigarh, Indiae. 15 Career Institute of Medical & Dental Sciences and Hospital, Lucknow, Indiaf. 16 School of Science, Monash University, Selangor DE, Malaysiag. 17 18 Running Head: Protein receptor for Influenza A Virus 19 20 # Corresponding author: Professor of Microbiology, School of Science, Monash University, 21 47500 Bandar Sunway, Selangor DE, Malaysia. 22 Email: [email protected]; Telephone: (+603) 551 59606 23 24 * Current address: Department of Pathogen Molecular Biology, London School of Hygiene & 25 Tropical Medicine, Keppel Street, London WC1E 7HT, United Kingdom. 26 1 bioRxiv preprint doi: https://doi.org/10.1101/104026; this version posted January 30, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
Antibodies to Watch in 2021 Hélène Kaplona and Janice M
MABS 2021, VOL. 13, NO. 1, e1860476 (34 pages) https://doi.org/10.1080/19420862.2020.1860476 PERSPECTIVE Antibodies to watch in 2021 Hélène Kaplona and Janice M. Reichert b aInstitut De Recherches Internationales Servier, Translational Medicine Department, Suresnes, France; bThe Antibody Society, Inc., Framingham, MA, USA ABSTRACT ARTICLE HISTORY In this 12th annual installment of the Antibodies to Watch article series, we discuss key events in antibody Received 1 December 2020 therapeutics development that occurred in 2020 and forecast events that might occur in 2021. The Accepted 1 December 2020 coronavirus disease 2019 (COVID-19) pandemic posed an array of challenges and opportunities to the KEYWORDS healthcare system in 2020, and it will continue to do so in 2021. Remarkably, by late November 2020, two Antibody therapeutics; anti-SARS-CoV antibody products, bamlanivimab and the casirivimab and imdevimab cocktail, were cancer; COVID-19; Food and authorized for emergency use by the US Food and Drug Administration (FDA) and the repurposed Drug Administration; antibodies levilimab and itolizumab had been registered for emergency use as treatments for COVID-19 European Medicines Agency; in Russia and India, respectively. Despite the pandemic, 10 antibody therapeutics had been granted the immune-mediated disorders; first approval in the US or EU in 2020, as of November, and 2 more (tanezumab and margetuximab) may Sars-CoV-2 be granted approvals in December 2020.* In addition, prolgolimab and olokizumab had been granted first approvals in Russia and cetuximab saratolacan sodium was first approved in Japan. The number of approvals in 2021 may set a record, as marketing applications for 16 investigational antibody therapeutics are already undergoing regulatory review by either the FDA or the European Medicines Agency.